According to The Times Higher Education World University Rankings 2012-2013, the highest ranked university in Africa, the University of Cape Town, is 113th in the world. The ranking system employs 13 performance indicators that take into account universities’ core functions, including “research, knowledge transfer and international outlook.” Among the leading 400 world academic institutions, there are only four from Africa, all in South Africa. As a region, Africa only has 35 scientists and engineers per million inhabitants, compared with 168 in Brazil, 2,457 in Europe and 4,103 in the United States. The region is clearly behind as far as knowledge production and dissemination is concerned, producing only 1.1 percent of the world’s scientific knowledge, despite comprising more than 13 percent of the global population.

At barely over 8 percent, Africa’s gross enrollment in tertiary institutions of learning is the lowest of any region in the world (UNESCO, 2011). The average enrollment rate for developing countries is 23 percent, and that for advanced countries is 74 percent. Africa’s poor showing in the higher education sweepstakes is both a cause and effect of the region’s poor economic environment. The massive cuts in higher education funding in the wake of the structural adjustment programs of the 1980s and 1990s, even as enrollment more than tripled between 1991 and 2005, have had an adverse impact on quality. And in turn, the lack of high quality tertiary level education has starved the region of high skills needed for efficient allocation of factors of production thereby stunting improvement in productivity, high value addition and research and development. Africa devotes less than 1 percent of its GDP to research and development.

Data from 33 countries for which it is available show that tertiary education financing in the region has declined from a high of US $6,800 per student per year in 1980 to just about $981 in 2005. Over the same period the World Bank decreased its education lending from 17 percent in 1985-89 to just 7.5 percent currently (this is despite the fact that the World Bank nearly doubled its education lending between 2008 and 2009). The decline in public funding in the face of increasing demand for higher education has led to the proliferation of private universities of dubious standards and a bias towards perceived “soft” fields. In 2004 a meager 28 percent of students were enrolled in perceived “hard” disciplines in the sciences and engineering.

A 2008 study of 12 countries showed an increase in public universities from 113 to 188 between 1995 and 2008. Over the same period private universities ballooned from 14 to 107. This rapid increase in the number of universities in the region has not been matched by an increase in the number of trained teaching staff or facilities such as laboratories, libraries, and the like. Indeed, most of the new universities have tended to specialize in vocational subjects that require very little capital and human resource investment. To put it mildly, there is a great mismatch between the region’s development needs and the type of graduates it produces each year.

An impression of the proposed Konza City in Kenya

The shortage of skills permeates nearly all skill levels, and could get worse as the region’s economy continues to grow over the next two decades. The case of Kenya is illustrative. The country has an ambitious plan to be the information and communication technology (ICT) hub of Eastern Africa (dubbed the “Silicon Savannah”) complete with a proposed $10 billion techno-city (Konza City) situated about 60 kilometres southeast of Nairobi. Already ICT multinationals, including IBM, Microsoft, Google and Intel, have their regional headquarters in Kenya. All this sounds good, except the lack of local skills. IBM’s research lab in Kenya has had to source for top talent among graduates in computer science, electrical engineering, mathematics, and data scientists from American universities. There is still a shortage of required skills among graduates of Kenyan universities. Quality assurance is also lacking, as recent news reports of “theses for hire” have demonstrated.

As the Kenyan case suggests, the lack of sufficient investment in high quality tertiary education has adversely impacted Africa’s ability to realize its economic potential. A 2005 study showed that a one-year increase in the higher education stock of the region could boost growth rate by about 0.63 percentage points. This adds up to an overall increase in income by about 12 percent over five years. For the region to take off economically there is need for greater investment in quality higher education that will train workers for the 21st century economy. But improving the quality of higher education in the region will be a very costly affair. On their own, the region’s countries lack both the resources (on account of their small economies) and demand (on account of their population sizes) to justify the types of investments required. This is where regional cooperation comes in.

Cross-border educational exchanges are not new in Africa, and go back to the pre-independence era. For generations non-Senegalese francophone students have studied in Senegal, seen as a cheap way of getting quality education at par with diplomas from France. Uganda, with East Africa’s top university, Makerere, hosts legions of Kenyan students, eager to avoid congestion and high costs back home. South Africa, with its many quality institutions is also a preferred destination for students from across the continent. These historical cross-border exchanges have led to the formation of regional associations of higher education – the francophone Conseil Africain et Malgache pour l’Enseignement Superieur (CAMES); Inter-University Council of East Africa (IUCEA); Southern African Regional Universities Association (SARUA); and inter-university cooperation under the Arab Maghreb Union (AMU). Continent-wide, the 208-member Association of African Universities (representing 45 countries) is the umbrella organization of the region’s institutions of higher learning.

These associations need to be strengthened and empowered as drivers of regional harmonization of higher education both to facilitate cross-border inter-university mobility of both teachers and students and guarantee quality assurance. As a 2007 World Bank report aptly noted, “regional quality assurance networks are particularly relevant to Africa because of human resource constraints.” On this score the European Higher Education Area provides a possible model. The just over 10 years old Bologna process is working towards ensuring inter-university mobility (in terms of courses, qualifications, and periods of study) as well as a uniform quality assurance standard. In the African context, a continent-wide area of higher education is infeasible because of language and logistical constraints. However, sub-regional areas of higher education, based on the existing associations, provide a possible avenue to invest in a few good institutions of higher learning that can have a demonstrative effect on national institutions as well set high standards of learning. The associations themselves can also serve as certification bodies to ensure a uniform quality assurance standard (see here).

The announcement in late July 2013 of the creation of a new US $154.2 million multinational science, innovation and technology Pan African University (PAU) in the next five years is therefore welcome. (The African Development Bank (AfDB) has pledged a $45 million grant towards the effort.) PAU will be structured around existing institutions of higher learning across Africa’s five sub-regions. Basic sciences, technology and innovation will be based in East Africa; earth and life sciences including health and agriculture in West Africa; governance, humanities and social sciences in Central Africa; water and energy sciences including climate change in North Africa; and space sciences in Southern Africa.

Thus far, discussions over regional integration of systems of higher education have tended to view tertiary institutions as tools for regional economic and political integration – be it in East Africa, Europe or East Asia. However, the creation of stronger regional areas of higher education – especially in a region like Africa – can also be an economically efficient way of facilitating greater investment in higher education to match the demands of a 21st century economy. It is encouraging that current trends signal a move in this direction. University systems in Africa’s sub-regions would be a good place to start.

I conclude with a caution. The rapid increase in the number of public and private universities in Africa over the last two decades has come at the expense of other post-secondary institutions of learning such as polytechnics (this shift has occurred to a lesser extent in francophone Africa than anglophone Africa). In many countries governments have simply converted polytechnics and other constituent colleges into fully-fledged universities. This trend is worrying, especially given the fact that the vast majority of high school leavers on the continent do not make it to university. The low quality of high school education in the region (as demonstrated by the recent mass student failures in Liberia and Tanzania) is yet another reason why these “bridge” tertiary institutions are needed, both to prepare students for university and to impart valuable skills for those that do not eventually make it to university.

The rush to invest in university education should not distract from the fact that vocational post-secondary institutions, such as polytechnics, are an important component of human capital development, even in advanced countries as is the case in Germany (with its impressive “dual system” of training codified in the Vocational Training Act of 1969). As African economies move from dependence on primary commodities to manufacturing and technology, there will be need for skilled workers at all occupational levels. Doing away with vocational post-secondary institutions will only serve to further inhibit the development of adequate and relevant human capital to match the increased demand for skilled workers.

OK, so as promised, here is my first attempt at looking at the numbers and what they are telling us about the outcome of the March 4th general election in Kenya.

14.3 million Kenyans registered to vote this year. Out of this (based on historical turnout rates) about 11 million will actually show up to vote. If the opinion polls are right, neither Uhuru Kenyatta nor Raila Odinga (the top two frontrunners) will get the requisite 50% plus one vote required to win the election. It is likely that there will be a runoff. About 4% of voters remain undecided. The polling trend (see below) suggests that the race will tighten over the next six weeks before the election.

The first opinion polls after the party nominations show Deputy Prime Minister Uhuru Kenyatta ahead of Prime Minister Raila Odinga in the raw vote, at least according to my analysis. The overall national head to head match up in the two polls released Monday show Mr. Odinga leading Mr. Kenyatta by (48-40, Infotrak) and (40-36, Ipsos).

The regional poll tallies, on the other hand, show a different story. In these Mr. Kenyatta emerges with a lead of between 490,000 and 630,000 of the accounted for votes depending on the turnout models used. The average of the tallies show that if elections were held over last weekend Mr. Kenyatta would garner 4.5 million votes to Mr. Odinga’s 3.9. This leaves about 24% of the (potential) votes cast either spread out among the other presidential contenders or undecided.

Here is how I arrived at the numbers:

The surveys by Infotrak and Ipsos (the two firms correctly predicted the outcome of the 2010 referendum) gave regional tallies of how the top two coalitions did among those surveyed. With a few modifications (like assigning the GEMA counties in Eastern region the Central region poll results), I assigned these tallies to the different counties within the regions. I then estimated voter turnout using the numbers from the three most recent national voting exercises – 2002 and 2007 elections and the 2010 referendum. Because of the anomalies in the presidential election in 2007, I used the constituency turnout figures (In these figures, for instance, Juja and Nithi did not have turnouts exceeding 100% as was the case in the presidential election in 2007). Of course there are counties in which the popularity of either Kenyatta or Odinga vary by constituency but this is the best we can do for now. I then used the estimated county turnout rate and the regional polling results to estimate the expected vote count for either candidate in each county using IEBC’s figures of registered voters.

It is important to note that among the two polls, Infotrak asked respondents about their preferred ticket (Kenyatta and Ruto vs. Odinga and Musyoka) while Ipsos asked about individual presidential candidates. The discrepancy in the national polling average and the raw numbers I show here might be because of incorrect weighting of the different regions by the polling companies. The fact that Kenyans vote along ethnic lines and voters are geographically concentrated means that the regional polling numbers might provide a better picture than the national numbers. National polls appear to be over-estimating Odinga’s support by about 3 percentage points on average.

Uhuru Kenyatta is ahead in the raw figures for the following reasons:

The first reason is that Mr. Kenyatta has the numbers. The combined GEMA registered voters number 3.9 million. That is 27.3% of the registered voters. Mr. Kenyatta obviously won’t bag 100% of these votes but it doesn’t hurt to have a vote rich base.

His stronghold of the wider Mt. Kenya region had the highest voter registration rate in the country. This, combined with the fact that his running mate brings in the populous Rift Valley region, gives Kenyatta a slight edge off the gates.

Kenyatta’s strongholds (Mt. Kenya) and Rift Valley have historically had higher turnout rates than the regions that Odinga will need to win on March 4th. In 2002 Kenyatta’s strongholds had a higher turnout rate by 5 percentage points. In 2007 it was 10%.

The combined high population, higher registration rates and expected higher turnout means that Mr. Kenyatta is presently the favorite to win the first round of the March 4th presidential poll.

How can Odinga win?

A lot of voters (24%) remain spread out among the smaller candidates or are undecided. Come election day these voters may break for Mr. Odinga for the reasons I gave in an earlier post.

Mr. Odinga’s other path to victory is by ensuring high turnout in his strongholds of Nyanza, Western and Coast regions. Just by matching the expected turnout in Mr. Kenyatta’s strongholds he would reduce the deficit to about 250,000 votes.

He must also eat into some of Mr. Kenyatta’s support in the Rift Valley and Central regions. If the election is a mere census then Mr. Kenyatta will win the first round (the second round is another story all together). For Mr. Odinga to win he must convince voters in Mr. Kenyatta’s strongholds that he is the better candidate.

Facing reality:

For a while it seemed like this election was Mr. Odinga’s to lose. I have since softened on this a little bit. Despite his many problems, Mr. Kenyatta can still win this election, at least the first round. In the second round everything will be contingent on who between Messrs Kenyatta and Odinga can bag the roughly 20% of votes that will go to various smaller candidates in the first round. As things stand Mr. Odinga is the likely beneficiary of these votes.

A lot will happen between now and March 4th. But key things to consider include:

If turnout is low on March 4th Mr. Kenyatta will emerge the winner. His (national) base is relatively wealthier and more urban (or more accurately, more politically engaged – if you doubt this see the voter registration numbers for Kiambu county alone) than Mr. Odinga’s and thus will have a higher turnout. Having failed to match Mr. Kenyatta’s voter registration rates, Mr. Odinga needs upwards of 80% of those registered in his strongholds to show up to vote, or else he will lose.

Mr. Kenyatta appeared to be the better organized candidate in getting his base to register to vote. And given the way in which his party handled the nominations exercise, it is likely that he will out-organize Mr. Odinga in getting his supporters to the polls. This spells more trouble for Mr. Odinga.

The nominations exercise gave Mr. Odinga’s coalition bad press for four consecutive days. His home base of Nyanza was the worst affected. Seemingly undemocratic nomination exercises – in which Odinga’s allies controversially won party primaries – in the region may depress turnout, something that Odinga should be worrying about A LOT. Watch out for how Mr. Odinga’s party handles the nominations fallout in his Nyanza backyard.

Musalia Mudavadi appears to have made gains in Western province – he is polling there at 26%. His gain is Odinga’s loss. If Mr. Mudavadi continues to gain in the next 40 days then we shall almost be assured of a run off, after Mr. Kenyatta wins the first round.

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